1. Field of the Invention
This invention relates to a method and system for computer-aided detection (CAD) of volumetric images, specifically for detection of polyps indicative of colon cancer in computed tomography imagery.
2. Discussion of Background
Colorectal cancer is the second leading cause of cancer death in the United States. Each year approximately 150,000 people are diagnosed with colon cancer and 56,000 people die from it. Colonoscopic removal of identifiable polyps can considerably decrease the mortality. However, current screening methods of fiberoptic colonoscopy, flexible sigmoidoscopy, fecal occult blood testing and barium enema examination carry varying amounts of risk and may cause considerable discomfort to the patient, and therefore are not widely accepted by the general population. Recently, non-invasive virtual colonoscopy (VC) systems using computed tomography (CT) images were introduced as a colon cancer screening method and several commercial systems have been approved by the FDA.
In a VC system, prone and supine CT views of air-filled and cleansed colon are acquired and displayed in two dimensions (2D) and in three dimensions (3D). Two-dimensional displays are usually transverse images of CT slices as well as sagittal and coronal reformations. Three-dimensional displays could be volume renderings of suspicious regions or endoluminal representations.
Because of the large number of images that need to be examined in 2D views (300-700 images/patient) and the relatively long time it takes to do an endoluminal “fly-through,” virtual colonoscopy interpretation can be quite time-consuming, typically ranging from 15 to 40 minutes when performed by experts in abdominal imaging. Additionally, the main task of identifying polyps can be challenging. Different studies report a large variation in sensitivity and specificity for the same dataset. This variation can be partly attributed to the operator's learning curve with the VC system. A CAD system can help users of VC systems by indicating the locations and reporting the characteristics of potential polyps. Such a system may increase the sensitivity while not decreasing the specificity.
It is therefore an object of this invention to provide a method and system for the automated detection of abnormal lesions in volumetric imagery.